AD ML Platform Engineer (Autonomous Driving)

Location: Hybrid at Pangyo (Software Dream Center), South Korea

Company

Develops autonomous driving systems and the data and machine learning platforms that support their development lifecycle.

What you will do

• Set the technical strategy and oversee development of a scalable, reliable data platform for managing, visualizing, and serving large-scale autonomous driving datasets.
• Build a data lakehouse for sensor, calibration, and annotation data covering millions of driving scenes.
• Develop the Autonomous Driving Data SDK for scene search, dataset preparation, and dataset loading.
• Investigate performance bottlenecks across data processing, data search, and test procedure coverage.
• Bootstrap and maintain data platform infrastructure, including processing pipelines, databases, lakehouses, and data serving.
• Align ML platforms with the autonomous driving system architecture in collaboration with ML algorithm, ML application, and cloud infrastructure teams.

Requirements

• Bachelor’s degree or higher in Computer Science, Engineering, Robotics, or a related technical field.
• At least 7 years of experience in data engineering or ML platform roles.
• Expert-level Python proficiency and substantial experience developing Python SDKs.
• Professional experience with databases such as MongoDB or PostgreSQL, data orchestration with Databricks Workflows or Apache Airflow, and big data engines such as Apache Spark.
• Strong knowledge of modern AI frameworks such as PyTorch or TensorFlow, including distributed data loaders for model training.
• Experience with data warehouse or lakehouse architectures, autonomous vehicle sensor data, ML model training lifecycles, data governance, privacy, security, and large models such as VLMs.

Nice to have

• Experience with LiDAR, camera, or radar data from autonomous vehicles.
• Experience implementing data security measures and governance controls.
• Understanding of large vision-language models.

Culture & Benefits

• Work in a cross-functional engineering environment spanning autonomous driving, machine learning, and cloud infrastructure.
• A 3-month probationary period may apply.
• Veterans and applicants eligible for employment protection receive consideration under applicable laws.
• Registered individuals with disabilities receive preferential consideration in accordance with applicable regulations.

Hiring process

• Application screening followed by a coding test.
• First interview: virtual, approximately one hour.
• Second interview: in-person or virtual, approximately three hours, followed by offer discussion and onboarding. A reference check may be conducted with consent.